This project aims to use leadership computing resources to simulate and reconstruct neutrino interactions and the cosmic-ray backgrounds that contaminate the readout of liquid argon time projection chambers. It will also develop tools to enable fast reprocessing and quick turnaround times to optimize the performance of the reconstruction and the precision of detector simulations.

This project aims to enable real-time compressed sensing tomography by developing a dynamic tomography framework that performs in-situ reconstruction as new data are collected.

Numerical simulations of the physical processes that occur in materials when they are excited with light are essential for the understanding and rational design of broad classes of materials. This project seeks to develop an AI-informed computational framework that integrates machine learning into existing workflows, thereby enabling the prediction of spectroscopic signatures of materials with fast turnaround.

This project leverages the Theta supercomputer to predict ultrafast function-property-structure relationships that dictate light control of emergent material properties in complex nanostructures composed of three classes of advanced functional materials: (1) layered-material heterostructures and magic-angle heterostacks; (2) novel chalcogenide perovskites; and (3) topological skyrmions superlattices.

This project focuses on the development, application, validation, and dissemination of empirical parameter-free methods and open-source codes to predict and explain the properties of functional materials for energy applications. To demonstrate a truly predictive and validated framework, it performs calculations on complex materials that possess a wide spectrum of properties, benefiting both fundamental science and new electronics, energy storage, conversion, and quantum technologies.

Core-collapse supernovae dramatically announce the death of massive stars and the birth of neutron stars. This multi-year INCITE project addresses whether and how 3D supernova explosion models differ from their 2D counterparts.

This work aims to advance our understanding of the physical mechanisms that drive the large mass loss rate for Wolf-Rayet (WR) stars—stars that are hotter and typically have a higher Eddington ratio than the massive stars studied in previous INCITE allocations.

This project aims to show, in silico and using massively parallel pseudo-spectral particle-in-cell simulations, that relativistic plasma mirrors can provide a simple and common elegant solution to three long-standing challenges of ultrahigh-intensity (UHI) physics.

This work studies the kinetic evolution of laser-plasma instabilities on meaningful spatial and temporal scales directly relevant to various inertial fusion energy (IFE) scenarios. Using the popular particle-in-cell code OSIRIS, the research team is performing fully kinetic simulations that will help advance research at the National Ignition Facility and other IFE experiments.

This project investigates how supersonic wall-bounded turbulent flows are affected by the thermal wall boundary condition and how they interact with flexible walls. It will also consider the interaction between supersonic turbulent boundary layers and shockwaves in the presence of rigid and flexible walls, and will create highly resolved reference data for two such cases.

This multi-year INCITE project seeks to advance the understanding of the edge plasma physics critical to fusion reactors, with a focus on ITER, an international collaboration to design, construct, and assemble a burning plasma experiment that can demonstrate the scientific and technological feasibility of fusion.

With this INCITE project, researchers from the Southern California Earthquake Center (SCEC) are working to enhance their earthquake simulation and hazard mapping tools to provide the best possible information in terms of earthquake ground motion and seismic hazard.

This multi-year INCITE project is using DOE leadership computing resources to perform extreme-scale simulations aimed at transforming our understanding of supernovae. The team’s investigation involves carrying out 3D magnetohydrodynamics simulations with sophisticated multidimensional neutrino transport and the most realistic initial conditions ever adopted for core-collapse supernovae.

This project supports the Energy Exascale Earth System Model, a multi-laboratory project driven by three grand challenge questions, two of which are the focus of this project: (1) How will more realistic portrayals of the water cycle’s important features affect river flow and associated freshwater supplies at the watershed scale? (2) In cryosphere systems, what are the impacts of ocean-ice interactions on Antarctic ice shelf melting and the implications for ice sheet dynamics and sea level rise?

With this project, the researchers intend to advance their real-time time-dependent density functional theory-based approach so as to study electronic stopping processes of complex systems for which going beyond typical-linear response theory formalism is necessary.

This work will build a high-fidelity computational model of chromatin to investigate the interplay between different folding mechanisms and to decipher the effects of genetic and epigenetic codes on the self-organization of the human genome. It will also extend the current static model into a dynamic one that leverages the dynamic PWS imaging technique developed in a previous INCITE allocation.

Building on previous INCITE research, this project will employ advanced ab-initio quantum many-body techniques coupled with applied mathematics and computer science methods to study a wide range of nuclei and to accurately describe the atomic nucleus from first principles.

The focus of this project is on developing the Nek5000, a leading high-order spectral element, open-source code for accurate modeling of fluid turbulence, into an effective exascale code for high-fidelity ICE simulations.

The Large Synoptic Survey Telescope (LSST), a ten-year imaging survey starting in 2022, is a cornerstone of the U.S. cosmological community’s efforts to understand dark energy, the cause of the accelerated expansion rate of the Universe. The infrastructure improvements that are developed for this simulation campaign are part of the longer path to science readiness undertaken by the LSST Darke Energy Science Collaboration.

This project will heavily exploit the GPU-capability of OLCF’s Summit for atomistic simulations and microstructure evolution software, which have proven to be highly efficient. Alloy design expertise and advanced characterization across multiple DOE national laboratories will actively support the proposed HPC ICME tasks. The outcome of this project is anticipated to fill critical knowledge gaps and shorten the timeframe from prototype automotive high-temperature alloys to their real-world deployment.